Behavioural framework for studying visually-directed reaching in the mouse
dc.contributor.advisor
Duguid, Ian
dc.contributor.advisor
Hennig, Matthias
dc.contributor.advisor
Surmeli, Gulsen
dc.contributor.advisor
Ludwig, Mike
dc.contributor.author
Colligan, Matt
dc.contributor.sponsor
Biotechnology and Biological Sciences Research Council (BBSRC)
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dc.date.accessioned
2024-10-04T13:39:06Z
dc.date.available
2024-10-04T13:39:06Z
dc.date.issued
2024-10-04
dc.description.abstract
Reaching and grasping are fundamental behaviours that humans and other mammalian
species depend on to perform useful interactions with our environment. To execute this
behaviour, forelimb movements require to be accurately targeted based on the
egocentric spatial position of objects of interest. As we navigate our environment, we
first visually identify the location of nearby objects, then use this information to
compute necessary movement trajectories. Decades of primate research has
successfully utilised reaching tasks to identify and characterise a number of brain areas
involved in visually-directed movement. Mice display a somewhat similar behavioural
repertoire to humans, including the ability to reach and grasp, and can therefore be
used as a model system to investigate neural control of movement. The improved
genetic tractability of mice has expanded our ability to delineate cell type- and pathwayspecific
functionality in the brain, and such research benefits from higher throughput
and lower financial cost. However, due to the lack of a suitable behavioural task, to date
there has been a distinct lack of research using mice to study visually-directed reaching.
To address this problem, I aimed to design a novel task for mice that researchers can
use to study this critical behaviour.
First, I designed and implemented a task in which freely moving mice learned to perform
visually-directed reaches. During the task, one of two reach targets was illuminated and
mice learned to reach and grasp the illuminated target to receive a water reward. Once
trained, mice would perform an initial reach to the visual stimulus followed by up to 10
repetitive, self-initiated reaches. Expert mice had a high success rate and performed an
average of 120 cued reaches per 30-minute session after 4 weeks of training.
Next, to take full advantage of the kinematic richness of the behaviour by enabling the
task to be combined with high temporal resolution extracellular recordings, I developed
a user-friendly data processing and analysis pipeline for electrophysiological data
collected using Neuropixels silicone probes. The pipeline, named pixels and opensourced
at https://github.com/DuguidLab/pixels, provides a simple Python API that
enables visualisation and statistical testing of neuron population extracellular activity
recorded during trial-based behavioural tasks. To enable high resolution examination of
the spatiotemporally detailed movements performed during the task and how they
relate to neural activity, pixels integrates closely with the DeepLabCut motion
tracking toolbox (Mathis et al., 2018).
Lastly, as a proof-of-concept demonstrating the utility of the visually-directed reaching
task, I performed extracellular recordings in expert mice and used pixels to examine
neural correlates of behaviour. Using chronically-implanted Neuropixels silicone probes,
I recorded population activity in posterior secondary motor cortex (pM2) and
dorsomedial striatum (DMS), brain areas implicated in visuomotor control (Hwang et al.,
2019; Itokazu et al., 2018) and goal-directed behaviour (Hwang et al., 2019; Wang et al.,
2013), respectively. In deep layers of pM2, over half of pM2 neurons exhibited
reproducible firing rate changes as mice initiated and executed visually-directed
reaches. During a 300 ms pre-reach window, a small proportion of pM2 neurons
displayed activity changes, suggestive of a role in movement preparation or initiation.
During reach execution, reduced firing rates dominated pM2 population activity in both
pyramidal cells and interneurons, while a small subset of pyramidal cells became more
active. Two competing models may explain this finding. The small excitatory component
may convey motor signals, with widespread inhibition possibly serving to improve the
signal-to-noise ratio in recipient areas. Alternatively, movement-related information may
be conveyed directly by the firing rate decreases, complementing the excitatory signals
to provide bidirectional modulation of recipient areas. Only approximately half of pM2
neurons active during cued reaches remained active during repetitive reaches,
suggestive of distinct motor pathways underlying these types of behaviours. Activity
profiles in DMS mirrored those in pM2, indicative of a close functional relationship
between the two areas. A quarter of DMS neurons active during cued reaches were also
active during repetitive reaches. As repetitive reaches had lower average peak velocities,
this finding is consistent with DMS regulating movement vigour according to expected
reward value (Wang et al., 2013). By identifying novel correlates between activity in these
brain areas and visually-directed reaching, this experiment demonstrates how the newly
developed task can yield new insights into the neural dynamics underlying this
behaviour.
In addition, I utilised pixels to analyse silicone probe recordings as part of
collaborative projects to investigate the neural underpinnings of forelimb motor control
in mice performing object manipulation tasks (Currie et al., 2022; Dacre et al., 2021). We
found that cerebellar-thalamocortical signals are required to shape motor cortical
activity and trigger movement in a behavioural context-dependent manner (Dacre et al.,
2021). Next, we examined how motor cortex encodes movement when mice perform
two distinct movements. We found that while movement-invariant responses dominated
layer 5B projection neurons, movement-specific activity is displayed by a small,
distributed population of layer 5B neurons and differentially between projection neuron
classes (Currie et al., 2022).
en
dc.identifier.uri
https://hdl.handle.net/1842/42257
dc.identifier.uri
http://dx.doi.org/10.7488/era/4977
dc.language.iso
en
en
dc.publisher
The University of Edinburgh
en
dc.relation.hasversion
Dacre, J., Colligan, M., Clarke, T., Ammer, J.J., Schiemann, J., Chamosa-Pino, V., Claudi, F., Harston, J.A., Eleftheriou, C., Pakan, J.M.P., Huang, C.-C., Hantman, A.W., Rochefort, N.L., Duguid, I., 2021. Neuron 109, 2326-2338.e8. https://doi.org/10.1016/j.neuron.2021.05.016
en
dc.relation.hasversion
Currie, S.P., Ammer, J.J., Premchand, B., Dacre, J., Wu, Y., Eleftheriou, C., Colligan, M., Clarke, T., Mitchell, L., Faisal, A.A., Hennig, M.H., Duguid, I., 2022. Cell reports (Cambridge) 39, 110801-110801. https://doi.org/10.1016/j.celrep.2022.110801
en
dc.relation.hasversion
Dacre, J., Colligan, M., Clarke, T., Ammer, J.J., Schiemann, J., Chamosa-Pino, V., Claudi, F., Harston, J.A., Eleftheriou, C., Pakan, J.M.P., et al. (2021). A cerebellar- thalamocortical pathway drives behavioral context-dependent movement initiation. Neuron 109, 2326–2338. https://doi.org/10.1016/j.neuron. 2021.05.016
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dc.subject
visually-directed reaching
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dc.subject
mouse
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dc.subject
visually-directed reaching in the mouse
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dc.subject
Reaching
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dc.subject
grasping
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dc.subject
neural control of movement
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dc.subject
freely moving mice
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dc.subject
visually-directed reaches
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dc.subject
posterior secondary motor cortex (pM2)
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dc.subject
dorsomedial striatum (DMS)
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dc.subject
visuomotor control
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dc.subject
object manipulation tasks
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dc.subject
cerebellar-thalamocortical signals
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dc.title
Behavioural framework for studying visually-directed reaching in the mouse
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dc.title.alternative
A behavioural framework for studying visually-directed reaching in the mouse
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dc.type
Thesis or Dissertation
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dc.type.qualificationlevel
Doctoral
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dc.type.qualificationname
PhD Doctor of Philosophy
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